Triple
T11576918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Bound |
E274528
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Paris Bound |
E274528
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Paris Bound | Statement: [Paris Bound, hasTitle, Paris Bound]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paris Bound Context triple: [Paris Bound, hasTitle, Paris Bound]
-
A.
Paris Bound
chosen
Paris Bound is a 1927 stage comedy by American playwright Philip Barry that explores modern marriage and sexual freedom among sophisticated New Yorkers.
-
B.
Paris Bar
The Paris Bar is the professional association and regulatory body for lawyers practicing in Paris, France.
-
C.
Mon Paris
Mon Paris is a modern, fruity-floral women’s fragrance by Yves Saint Laurent Beauté known for its sweet, sensual scent and chic, contemporary Parisian style.
-
D.
Paris Qualles
Paris Qualles is an American television and film screenwriter and producer known for his work on socially conscious dramas and biographical projects.
-
E.
Town of Paris
The Town of Paris is a small rural municipality located in Kenosha County, Wisconsin, known for its agricultural landscape and quiet residential character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89049721081909278adfada668ef9 |
completed | April 10, 2026, 5:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e713f7ca4c81908f29143df420fd71 |
completed | April 21, 2026, 6:06 a.m. |
Created at: April 8, 2026, 9:38 p.m.